The adoption of analytics has accelerated over the last decade, and most organisations have created or developed an analytics function to drive insight from data. However, organisations often face challenges in being able to deliver true business value through their analytics team, and it can be difficult to obtain the right blend of skills to make sure the team is set up for success. In this talk, I’ll share my experience of working in analytics functions in both consulting and in industry and will share thoughts on what creates an effective analytics team, considering the important skills and capabilities that can drive success and add true value to an organisation.

Elizabeth is the Head of Analytics and BI for Aggreko, and leads a team of data scientists who use data to drive value across the business. She has spent the last 12 years working in a variety of industries, helping them use their data to solve business problems. She has a passion for helping people understand the value of data, and loves to communicate complex ideas in a simple way to enable effective insight-driven decision making.

Uplift modelling is a different approach to customer targeting that directly predicts the *change* in customer behaviour—how much more likely a customer is to stay, or to buy, if treated, compared with if they are not. This talk will explain what uplift modelling is, how it works, and show some real-world results, as well as discussing the applicability of the method and offering some tips on how to get the most out of it.

Targeting with uplift models typically generates more sales or more saved customers, while treating fewer of them thus reducing costs. It also helps to identify customers who should definitely not be treated because of negative effects e.g triggering customer attrition.

Nick is a practising data scientist with over 30 years experience, from neural networks and genetic algorithms on parallel systems in the late 1980s, through parallel machine learning and 3D visualisation software as a founder of Quadstone, from 1995, to novel modelling methods (e.g. uplift modelling) in the early 2000s. Since 2007, he has run Edinburgh data science specialists Stochastic Solutions.

Nick enjoys using his deep knowledge of underlying algorithms to fashion tailored solutions to practical business problems for clients including Barclays, Sainsburys, T-Mobile and Skyscanner, and has a particular interest in testing and correctness in data science.

Nick is also a Visiting Professor of Mathematics at Edinburgh University.

This is a group for anyone interested in Data Science, Big Data, Analytics and Technology trends. We started this group to build a community to discuss general insights into the market and share personal experiences of working and operating in this area. We hope to cover skills shortages, technological advancements and organisational implications in Data Science and Technology during our series of meetups. All skill levels are welcome.